VACT: Visualization-aware CT reconstruction

Computed tomography (CT) reconstruction methods are often unaware of the requirements of the subsequent 3D volume visualization stage. In this stage, a delicate and often-studied component is the interpolation of off-grid samples, where aliasing can lead to misleading artifacts and blurring, potentially hiding fine details of critical importance. The visualization-aware CT reconstruction framework we describe aims to account for these errors directly in the volume generation stage. Our framework informs the CT reconstruction process of the specific filter intended for interpolation in the subsequent visualization process, and this in turn ensures an accurate interpolation there at a set tolerance. Here, we focus on fast trilinear interpolation in conjunction with an octree-type mixed resolution volume representation without T-junctions. Efficient rendering is achieved by a space-efficient and locality-optimized representation, which can straightforwardly exploit fast fixed-function pipelines on GPUs.